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Data modeler - insurance

London
Korn Ferry
Insurance
Posted: 1 September
Offer description

This role will be critical in standardising and unifying disparate data sources, supporting the implementation of a modern Medallion Architecture (Bronze, Silver, Gold layers) on a cloud data platform (Snowflake), and enabling scalable, business-aligned data structures that underpin analytics, reporting, and operational efficiency.,

* Design and maintain conceptual, logical and physical data models for enterprise use.
* Translate business requirements into robust data structures that support reporting, analytics, and operational systems.
* Develop and maintain a common data dictionary and ensure consistency of definitions across the enterprise.
* Collaborate with business stakeholders, data architects, data engineers, and analysts to ensure alignment of models with business needs.
* Support the design and implementation of Medallion Architecture data layers, ensuring consistent transformation from raw to curated datasets.
* Apply best practices in data governance, data quality, and master data management.
* Document modelling standards, methodologies, and design decisions.
* Present and explain data models to technical and non-technical audiences.

10+ years of data modelling experience with proven expertise in conceptual, logical, and physical modelling.
* Strong background in London Market/broking insurance data domains (eg, policies, claims, premiums, reinsurance, underwriting).
* Deep knowledge of data modelling methodologies such as 3NF, dimensional modelling (star/snowflake schema), and data vault.
* Experience with data modelling tools (eg, ER/Studio, Erwin, PowerDesigner, Sparx EA).
* Hands-on experience with cloud data platforms (Snowflake preferred; AWS, Azure, or GCP experience beneficial).
* Solid understanding of data governance, data quality, and master data management principles.
* Familiarity with Agile delivery (Scrum, Kanban, SAFe) and tools such as JIRA.
* Excellent problem-solving skills and attention to detail.
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